Statistics for Data Science with R

• About this course

• Acknowledgements

• Basic Statistics
• Descriptive Statistics
• Distributions
• Inferential Statistics
• Linear Models
• Introduction
• t-test, ANOVA
• Regression
• Complex Linear Models
• Some Theory on LM
• Generalized Linear Models
• Introduction
• Binomial
• Poisson
• Gamma
• Some Theory on GLM
• Other GLM
• Introduction
• Multinomial Logistic
• Ordered Logit Model
• Negative Binomial Model
• Some Theory on other GLM
• Other Models
• Neural networks,GAM, ...
• Appendices
• Diagnostics
• AIC
• Sum of Squares
• Fixed Effects
• Nested ANOVA

Acknowledgements

This web book is the result of work of my colleagues:

• Enrico Pegoraro, who wrote all previous versions of this book
• Veronica Giro, who reviewed and reassembled all these materials.

However, it would not have been possible without the sharing of knowledge, information, ideas, doubts and even criticisms of many individuals on the internet. I would like to extend my sincere thanks to all of them.

Andrea Spanò,
Quantide s.r.l.